Currently, wireless services are getting more importance, and demand on higher network capacity and performance keeps growing. On the other hand, several current solutions, such wider frequency band, optimal modulation scheme, and even code multiplexing system has a limited potential in improving spectrum efficiency.
A Multiple Input Multiple Output (MIMO) system uses an antenna array and thus space multiplexing technology to improve bandwidth usage efficiency. In many reality applications, channel parameters can be obtained via a feedback channel between a receiver and a transmitter (given that feedback delay is far less than channel coherence time). In addition, in a TDD (time division duplex) system, if operations of data receiving and data transmitting is completed within a ping pong period, an estimation value of the channel in a receiving mode can be applied in a transmitting mode (given that the ping pong period is far less than channel coherence time). Therefore, there comes a problem that how to utilize channel estimation values to optimize a transmitter's transmitting scheme and accordingly to design an optimal receiver. At present, studies in this respect include linear and nonlinear optimal pre-coding techniques. Although the nonlinear pre-coding method has a better performance than the linear pre-coding method, its implementation complexity is far higher than that of the latter. So, the linear pre-coding method is the mainstream under research. The linear pre-coding technique makes full use of all or part of CSI (Channel State Information) to obtain as much beam-shaping gain as possible.
In a MIMO system, the transmitter needs to obtain a pre-coding matrix if a pre-coding based processing will be implemented. There are two methods for obtaining a pre-coding matrix, one is that the transmitter obtains the pre-coding matrix after it obtains a channel matrix H from an uplink sounding signal transmitted by the receiver, and the other is that the transmitter obtains the pre-coding matrix from CQI (Channel Quality Indicator) or Pre-coded Matrix Index fed back from the receiver. In an FDD mode of a communication system, uplink and downlink communications occupy different frequency bands. In this case, only the second method, i.e., by feedback from the receiver, can be adopted to obtain information on the pre-coding matrix. While in a TDD mode, both of the above methods can be adopted to obtain the pre-coding matrix. In the TDD mode, if the transmitter can accurately obtain the pre-coding matrix, system performance can be improved, and the complexity in the receiver can be reduced. In the TDD mode, the CSI fed back in the second method has some quantization error, and such feedback requires much greater overhead. Therefore, the MIMO system tends to use the first method (i.e., by uplink sounding signal) to obtain channel matrix H in the TDD mode, and then obtain the pre-coding matrix. However, the number of antennas at the transmitter is greater than antennas at the receiver in a future MIMO system, and thus uplink and downlink antenna configurations does not matched with each other. Consequently, it is impossible for the transmitter to obtain complete channel state information (CSI) from the uplink sounding signal. This problem needs to be settled.
In a TDD mode, the transmitter can accurately obtain the pre-coding matrix V through two methods. The first method is that the transmitter performs SVD decomposition to the received channel matrix H, which is obtained from the uplink sounding signal transmitted by the receiver. The second method is that the transmitter obtains the pre-coding matrix from a codebook of quantized CSI fed back by the receiver. The second method is suitable for a FDD mode, since the uplink and the downlink occupy different frequency bands in a FDD mode, and no reciprocity exists between the uplink and downlink. So, only the method using CSI fed back from the receiver can be used to obtain the pre-coding matrix. On the other hand, in a TDD mode, the method using a codebook of CSI fed back from the receiver will be subjected to channel quantization error and much greater feedback overhead. This reason is that reciprocity exists between the uplink and downlink channel impulse responses in a TDD mode of a mobile communication system. Therefore, the downlink channel impulse response can be obtained by estimating that of the uplink. At present, for a MIMO-OFDM system in TDD mode, channel response is primarily estimated by inserting discrete pilot in a data frame. Unfortunately, in order to estimate channel impulse matrix H, it is necessary to interpolate the estimated discrete channel response, and it is impossible to obtain an accurate channel impulse matrix H.
In a TDD mode, it is possible to obtain a relatively accurate channel impulse matrix H by using the uplink sounding signal to support pre-coding. However, the number of antennas at the transmitter is greater than antennas at the receiver in a future MIMO system, and thus uplink and downlink antenna configurations are not matched with each other. Consequently, it is impossible for the transmitter to obtain complete channel state information (CSI) from the uplink sounding signal.